NNAR

Clase series de tiempo, primavera 2024

library(tidyquant)
library(tidyverse)
library(tsibble)
library(fable)
library(feasts)

index = tq_index("SP500") %>% select(symbol, weight)
index = index %>% filter(symbol != "-")
index
sum(index$weight)

data = tq_get(index$symbol, get = "stock.prices", from = "2023-01-01", to = "2024-03-29") %>% select(symbol, date, adjusted)

library(readxl)
sectores <- read_excel("Proyecto_2/sectores.xlsx")

index = left_join(index, select(Sector, c(Symbol, Sector)), by = join_by(symbol == Symbol))

index %>% filter(if_any(everything(), is.na))

symbols_from_data = unique(data$symbol)
data = pivot_wider(data, id_cols = date, names_from = symbol, values_from = adjusted)
data = mutate(data, t = row_number())
data = pivot_longer(data, all_of(symbols_from_data), names_to = "symbol", values_to = "adjusted")

data = data %>% group_by(symbol) %>% mutate(t = row_number())
data = as_tsibble(data, index = t, key = symbol)
data

data = left_join(data, index, by = join_by(symbol == symbol))
data

data = as_tsibble(data, index = t, key = symbol)

data = data %>% mutate(portafolio = adjusted*weight*100)

fcasts_symbol <- data %>%
  model(arima = ARIMA(adjusted)) %>%
  forecast(h = 20)

Warning: NaNs producedWarning: NaNs producedWarning: NaNs producedWarning: NaNs producedWarning: NaNs producedWarning: NaNs produced

fcasts_symbol

fcasts_symbol = left_join(fcasts_symbol, select(index, c(symbol,weight, Sector)), by = join_by(symbol == symbol))
fcasts_symbol = fcasts_symbol %>% mutate(portafolio = .mean*weight*100)

#fcasts_sector = fcasts_symbol %>% aggregate_key(Sector/symbol, portafolio = sum(portafolio))
fcasts_sector = fcasts_symbol %>% group_by(Sector) %>% summarise(portafolio = sum(portafolio))
fcasts_sector

portafolio_fcst = fcasts_sector %>% summarise(portafolio = sum(portafolio))
portafolio_fcst

groups

data_agg = data %>% aggregate_key(Sector/symbol, portafolio = sum(portafolio))

data_agg %>% filter(is_aggregated(symbol)) %>% autoplot(portafolio) + facet_wrap(vars(Sector), scales = "free_y", ncol = 3) + theme(legend.position = "none")

if_else(ets<arima,
       if_else(ets<harmonic,
               if_else(ets<prophet,
                       ets,
                       if_else(arima<harmonic,
                               if_else(arima<prophet,
                                       arima, 
                                       if_else(harmonic<prophet,
                                               harmonic,
                                               prophet
                                               )
                                       ),
                               harmonic
                                ),
                       ),
               if_else(harmonic<prophet,
                       harmonic,
                       prophet
                       )
                ),
        if_else(arima<harmonic,
               if_else(arima<prophet,
                       arima, 
                       if_else(harmonic<prophet,
                               harmonic,
                               prophet
                               )
                       ),
               harmonic
                ))

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